You\u27re In Kentucky Sure As You\u27re Born

https://digitalcommons.library.umaine.edu/mmb-vp/4993/thumbnail.jp

Evaluation of the i3 Scale-up of Reading Recovery | Year One Report, 2011-12

Reading Recovery (RR) is a short-term early intervention designed to help the lowest-achieving readers in first grade reach average levels of classroom performance in literacy. Students identified to receive Reading Recovery meet individually with a specially trained Reading Recovery (RR) teacher every school day for 30-minute lessons over a period of 12 to 20 weeks. The purpose of these lessons is to support rapid acceleration of each child's literacy learning. In 2010, The Ohio State University received a Scaling Up What Works grant from the U.S. Department of Education's Investing in Innovation (i3) Fund to expand the use of Reading Recovery across the country. The award was intended to fund the scale-up of Reading Recovery by training 3,675 new RR Teachers in U.S. schools, thereby expanding capacity to allow service to an additional 88,200 students.The Consortium for Policy Research in Education (CPRE) was contracted to conduct an independent evaluation of the i3 scale up of Reading Recovery over the course of five years. The evaluation includes parallel rigorous experimental and quasi-experimental designs for estimating program impacts, coupled with a large-scale mixed-methods study of program implementation under the i3 scale-up. This report presents findings through the second year of the evaluation. The primary goals of this evaluation were: a) to assess the success of the scale-up in meeting the i3 grant's expansion goals; b) to document the implementation of scale-up and fidelity to program standards; and, c) to provide experimental evidence of the impacts of Reading Recovery on student learning under this scale-up effort

Evolutionary Dynamics of Giant Viruses and their Virophages

Giant viruses contain large genomes, encode many proteins atypical for viruses, replicate in large viral factories, and tend to infect protists. The giant virus replication factories can in turn be infected by so called virophages, which are smaller viruses that negatively impact giant virus replication. An example are Mimiviruses that infect the protist Acanthamoeba and that are themselves infected by the virophage Sputnik. This paper examines the evolutionary dynamics of this system, using mathematical models. While the models suggest that the virophage population will evolve to increasing degrees of giant virus inhibition, it further suggests that this renders the virophage population prone to extinction due to dynamic instabilities over wide parameter ranges. Implications and conditions required to avoid extinction are discussed. Another interesting result is that virophage presence can fundamentally alter the evolutionary course of the giant virus. While the giant virus is predicted to evolve towards increasing its basic reproductive ratio in the absence of the virophage, the opposite is true its presence. Therefore, virophages can not only benefit the host population directly by inhibiting the giant viruses, but also indirectly by causing giant viruses to evolve towards weaker phenotypes. Experimental tests for this model are suggested

Host Density and Human Activities Mediate Increased Parasite Prevalence and Richness in Primates Threatened by Habitat Loss and Fragmentation

1. Habitat loss and fragmentation are the principal causes of the loss of biological diversity. In addition, parasitic diseases are an emerging threat to many animals. Nevertheless, relatively few studies have tested how habitat loss and fragmentation influence the prevalence and richness of parasites in animals. 2. Several studies of nonhuman primates have shown that measures of human activity and forest fragmentation correlate with parasitism in primates. However, these studies have not tested for the ecological mechanism(s) by which human activities or forest fragmentation influence the prevalence and richness of parasites. 3. We tested the hypothesis that increased host density due to forest fragmentation and loss mediates increases in the prevalence and richness of gastrointestinal parasites in two forest primates, the Tana River red colobus (Procolobus rufomitratus, Peters 1879) and mangabey (Cercocebus galeritus galeritus, Peters 1879). We focused on population density because epidemiological theory states that host density is a key determinant of the prevalence and richness of directly transmitted parasites in animals. 4. The Tana River red colobus and mangabey are endemic to a highly fragmented forest ecosystem in eastern Kenya where habitat changes are caused by a growing human population increasingly dependent on forest resources and on clearing forest for cultivation. 5. We found that the prevalence of parasites in the two monkeys was very high compared to primates elsewhere. Density of monkeys was positively associated with forest area and disturbance in forests. In turn, the prevalence and richness of parasites was significantly associated with monkey density, and attributes indicative of human disturbance in forests. 6. We also found significant differences in the patterns of parasitism between the colobus and the mangabey possibly attributable to differences in their behavioural ecology. Colobus are arboreal folivores while mangabeys are terrestrial habitat generalists

Simulation-based model selection for dynamical systems in systems and population biology

Computer simulations have become an important tool across the biomedical sciences and beyond. For many important problems several different models or hypotheses exist and choosing which one best describes reality or observed data is not straightforward. We therefore require suitable statistical tools that allow us to choose rationally between different mechanistic models of e.g. signal transduction or gene regulation networks. This is particularly challenging in systems biology where only a small number of molecular species can be assayed at any given time and all measurements are subject to measurement uncertainty. Here we develop such a model selection framework based on approximate Bayesian computation and employing sequential Monte Carlo sampling. We show that our approach can be applied across a wide range of biological scenarios, and we illustrate its use on real data describing influenza dynamics and the JAK-STAT signalling pathway. Bayesian model selection strikes a balance between the complexity of the simulation models and their ability to describe observed data. The present approach enables us to employ the whole formal apparatus to any system that can be (efficiently) simulated, even when exact likelihoods are computationally intractable.Comment: This article is in press in Bioinformatics, 2009. Advance Access is available on Bioinformatics webpag

Estimation of Exposure Distribution Adjusting for Association Between Exposure Level and Detection Limit

In environmental exposure studies, it is common to observe a portion of exposure measurements to fall below experimentally determined detection limits (DLs). The reverse Kaplan–Meier estimator, which mimics the well‐known Kaplan–Meier estimator for right‐censored survival data with the scale reversed, has been recommended for estimating the exposure distribution for the data subject to DLs because it does not require any distributional assumption. However, the reverse Kaplan–Meier estimator requires the independence assumption between the exposure level and DL and can lead to biased results when this assumption is violated. We propose a kernel‐smoothed nonparametric estimator for the exposure distribution without imposing any independence assumption between the exposure level and DL. We show that the proposed estimator is consistent and asymptotically normal. Simulation studies demonstrate that the proposed estimator performs well in practical situations. A colon cancer study is provided for illustration

Circulating exosomal microRNA expression patterns distinguish cardiac sarcoidosis from myocardial ischemia.

OBJECTIVE: Cardiac sarcoidosis is difficult to diagnose, often requiring expensive and inconvenient advanced imaging techniques. Circulating exosomes contain genetic material, such as microRNA (miRNA), that are derived from diseased tissues and may serve as potential disease-specific biomarkers. We thus sought to determine whether circulating exosome-derived miRNA expression patterns would distinguish cardiac sarcoidosis (CS) from acute myocardial infarction (AMI). METHODS: Plasma and serum samples conforming to CS, AMI or disease-free controls were procured from the Biologic Specimen and Data Repository Information Coordinating Center repository and National Jewish Health. Next generation sequencing (NGS) was performed on exosome-derived total RNA (n = 10 for each group), and miRNA expression levels were compared after normalization using housekeeping miRNA. Quality assurance measures excluded poor quality RNA samples. Differentially expressed (DE) miRNA patterns, based upon \u3e2-fold change (p \u3c 0.01), were established in CS compared to controls, and in CS compared to AMI. Relative expression of several DE-miRNA were validated by qRT-PCR. RESULTS: Despite the advanced age of the stored samples (~5-30 years), the quality of the exosome-derived miRNA was intact in ~88% of samples. Comparing plasma exosomal miRNA in CS versus controls, NGS yielded 18 DE transcripts (12 up-regulated, 6 down-regulated), including miRNA previously implicated in mechanisms of myocardial injury (miR-92, miR-21) and immune responses (miR-618, miR-27a). NGS further yielded 52 DE miRNA in serum exosomes from CS versus AMI: 5 up-regulated in CS; 47 up-regulated in AMI, including transcripts previously detected in AMI patients (miR-1-1, miR-133a, miR-208b, miR-423, miR-499). Five miRNAs with increased DE in CS included two isoforms of miR-624 and miR-144, previously reported as markers of cardiomyopathy. CONCLUSIONS: MiRNA patterns of exosomes derived from CS and AMI patients are distinct, suggesting that circulating exosomal miRNA patterns could serve as disease biomarkers. Further studies are required to establish their specificity relative to other cardiac disorders

Circular Stochastic Fluctuations in SIS Epidemics with Heterogeneous Contacts Among Sub-populations

The conceptual difference between equilibrium and non-equilibrium steady state (NESS) is well established in physics and chemistry. This distinction, however, is not widely appreciated in dynamical descriptions of biological populations in terms of differential equations in which fixed point, steady state, and equilibrium are all synonymous. We study NESS in a stochastic SIS (susceptible-infectious-susceptible) system with heterogeneous individuals in their contact behavior represented in terms of subgroups. In the infinite population limit, the stochastic dynamics yields a system of deterministic evolution equations for population densities; and for very large but finite system a diffusion process is obtained. We report the emergence of a circular dynamics in the diffusion process, with an intrinsic frequency, near the endemic steady state. The endemic steady state is represented by a stable node in the deterministic dynamics; As a NESS phenomenon, the circular motion is caused by the intrinsic heterogeneity within the subgroups, leading to a broken symmetry and time irreversibility.Comment: 29 pages, 5 figure

Evaluation of the i3 Scale-Up of Reading Recovery | Year Two Report, 2012-13

Reading Recovery is a short-term early intervention designed to help the lowest-achieving readers in first grade reach average levels of classroom performance in literacy. Students identified to receive Reading Recovery meet individually with a specially trained Reading Recovery teacher every school day for 30-minute lessons over a period of 12 to 20 weeks. The purpose of these lessons is to support rapid acceleration of each child’s literacy learning. In 2010, The Ohio State University received a Scaling Up What Works grant from the U.S. Department of Education Investing in Innovation (i3) Fund to expand the use of Reading Recovery across the country. The award was intended to fund the training of 3,675 new Reading Recovery teachers in U.S. schools, thereby expanding service to an additional 88,200 students. The Consortium for Policy Research in Education (CPRE) was contracted to conduct an independent evaluation of the i3 scale-up of Reading Recovery over the course of five years. The evaluation includes parallel rigorous experimental and quasi-experimental designs for estimating program impacts, coupled with a large-scale mixed-methods study of program implementation. This report presents the findings of the second year of the evaluation. The primary goals of this evaluation are: a) to provide experimental evidence of the impacts of Reading Recovery on student learning under this scale-up effort ; b) to assess the success of the scale-up in meeting the i3 grant’s expansion goals; and c) to document the implementation of the scale-up and fidelity to program standards. This document is the second in a series of three reports based on our external evaluation of the Reading Recovery i3 Scale-Up. This report presents results from the impact and implementation studies conducted over the 2012-2013 school year—the third year of the scale-up effort and the second full year of the evaluation. In order to estimate the impacts of the program, a sample of first graders who had been selected to receive Reading Recovery were randomly assigned to a treatment group that received Reading Recovery immediately, or to a control group that did not receive Reading Recovery until the treatment group had exited the intervention. The reading achievement of students in this sample was assessed using a standardized assessment of reading achievement—the Iowa Tests of Basic Skills (ITBS). The data for the implementation study include extensive interviews and surveys with Reading Recovery teachers, teacher leaders, site coordinators, University Training Center directors, members of the i3 project leadership team at The Ohio State University, and principals and first-grade teachers in schools involved in the scale-up. Case studies were also conducted in nine i3 scale-up schools to observe how Reading Recovery operates in different contexts